Spark (mathematics)

About: Spark (mathematics) is a research topic. Over the lifetime, 7304 publications have been published within this topic receiving 63322 citations.

Self contained multi-function engine monitor and timer for providing engine running time, job time, service time and tachometer functions

Abstract: An engine monitor includes, in a self-contained preferably sealed unit, a spark sensor, inductively and capacitively coupled through the case to a spark pick up wire, a timer, and a running time detector, responsive to inputs from the spark pick up to provide total running time, job time, and service time metering. Preferably, storage means are included for storing maximum RPM and spark mode data, that is, data indicating the number of firings per RPM for the particular engine, as well as a preset service interval and one or more auxiliary timers.

Performance Evaluation of Distributed Machine Learning for Load Forecasting in Smart Grids

Abstract: Load forecasting in smart grid is the process of predicting the amount of electrical power to meet the short, medium and long term demands. Accurate load forecasting helps electrical utilities to manage their energy production, operations, control and management. Most of the state-of-the-art forecasting methodologies utilize classical machine learning algorithms to predict the electrical load. There is a need that big data platforms and parallel distributed computing are utilized to their potential in the available solutions. In this paper, the Apache Spark and Apache Hadoop are utilized as big data platforms for distributed computing in order to predict the load using available big data. In this paper, MLib, Spark library for machine learning algorithms, is utilized for distributed computing. Using MLib allows testing the classic regression algorithms such as linear regression, generalized linear regression, decision tree, random forest and gradient-boosted trees in addition to survival regression and isotonic regression. The obtained results show that Spark produces high accuracy while parallelizing the process of load forecasting in highly competent training and test times. Actual big data are used in the load forecasting process.

New Aspects on Spark Ignition

Abstract: Fundamental investigations have been made on processes in common spark plugs useful for ignition of fuel-air mixtures. Development of spark discharge from the early beginnings as well as the initiation of chemical reaction have been studied experimentally by using very high frequency measuring technique, radiation measurements, spectroscopic methods and interferometry by a nitrogen laser (about 300 ps). The measurements have been carried out in non-reacting gases (N2, air) as well as in inflammable mixtures. A complete description will be given of the total process from the spark breakdown to the arc and glow-phase, resp., in the millisecond range including temperature, local dimensions, energy distribution and radicals which can be formed. /SASI/

Apparatus and methods for optical emission spectroscopy

Abstract: A spark generator suitable for use in an optical emission spectrometer, and capable of generating a spark in a spark gap formed between an electrode and a sample to be analyzed, comprises a generator for generating a current of programmable amplitude in the spark gap in each of a series of discrete time intervals. The spark generator according to the invention is advantageous when compared with conventional spark generators in that it enables a higher degree of choice and control in the form of the spark. In particular, it enables the amplitudes of various portions of the spark to be independently varied, thus permitting the shape of the spark to be tailored to the particular analysis being performed. Also described are methods of optical emission spectroscopy which make use of the advantageous properties of the spark generator.